Titlebook: Intelligent Data Analytics for Decision-Support Systems in Hazard Mitigation; Theory and Practice Ravinesh C. Deo,Pijush Samui,Zaher Mundh

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Ravinesh C. Deo,Pijush Samui,Zaher Mundher YaseenPresents novel applications of artificial neural networks to design practical alert systems for natural hazards.Offers concise theories and case studies on advanced data analytics for real-life decisi

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Springer Transactions in Civil and Environmental Engineeringhttp://image.papertrans.cn/i/image/469563.jpg

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Bayesian Markov Chain Monte Carlo-Based Copulas: Factoring the Role of Large-Scale Climate Indices n advanced statistical copula approach to model lag relationships between monthly Southern Oscillation Index (SOI), an ENSO indicator, and monthly Flood Index (FI) that can be used for flood prediction. Copula parameters were numerically derived from under a hybrid-evolution Markov chain Monte Carlo

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,Gaussian Naïve Bayes Classification Algorithm for Drought and Flood Risk Reduction,e variability. Consequently, intelligent data analytic models are increasingly harnessed as decision support tools. This chapter presents an intelligent data analytic technique for predicting several magnitudes of droughts and floods, as well as conditions that necessitate their occurrence based on

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Intelligent Data Analytics Approaches for Predicting Dissolved Oxygen Concentration in River: Extreersus random forest, MLPNN and MLR. Dissolved oxygen concentration (DO) in river, lake and stream can be measured directly in situ. However, mathematical models based on intelligent data analytic technique can provide a reasonably good alternative by linking several water quality variables to the co

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